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Navigating the complex HR technology landscape to your advantage

Author: Tatiana OhmDate: 13 November 2017

Technology has given a boost to many aspects of business operations, including HR practices. The time has come to examine closer the complex HR digital landscape and how technology boost organisations’ ability to attract talent, improve engagement for both candidates and employees, and deliver better recruitment outcomes.

In a survey by KellyOCG and Human Capital Media[i], the research arm of Workforce magazine, respondents were almost unanimous in believing that a wide range of recruiting tasks should be automated. One in five organisations plan to use Artificial Intelligence (AI) within the next two years, while others want to explore digital scheduling and automated onboarding.

As more companies turn to digital solutions to improve their recruitment processes, early adopters will be well positioned to get their pick of hires. Being able to identify the best fit versus the first fit will give such organisations a decisive advantage.

However, this opportunity comes with obstacles. Survey respondents cite a lack of budget, difficulty securing leadership buy-in, and complexity in measuring the impact or return on investments such technologies can deliver. A proliferation of systems and how to make sense of the data does not improve the situation.

After reviewing the technology landscape, three technologies look particularly promising[ii].

Robotic Process Automation (RPA)

RPA software is a good place to start for companies wanting to introduce technology to their HR processes. Where rules and logic can be applied, RPA does the work much faster with fewer errors.

Relatively easy to deploy, RPA can be used for tasks spanning multiple systems. An example is onboarding, transferring and off-boarding, where actions need to be taken in benefits, payroll and pension administration systems. Automation will reduce the tedium of such processes.

Predictive Analytics

Predicting the future might seem like the holy grail. While big data cannot yet tell us everything, the use of statistical models on data to forecast trends is well established.

Predictive analytics is the use of software to build these models, testing them against actual behaviour to confirm their validity and implementing them to give results. Managers will then have to act on the results to generate desired outcomes.

For instance, reducing attrition by just 1 per cent in an organisation of 5,000 employees with an attrition rate of 10 per cent can save $3.75 million. If voluntary attrition can be predicted, steps can be taken to prevent it or lessen its impact.

Artificial Intelligence

AI is set to revolutionise business practices, including the field of HR. AI applications in HR such as spotting gender bias in recruiting and predicting turnover through sentiment analysis already exist, drawing on data from call records, social media and internal data to make its predictions.

Software vendors are creating systems to help hiring managers decide which candidates to pursue, and can suggest what interview questions to pose. It does this by comparing metrics of employees already succeeding in the company to those in the candidate pool.

By automating repetitive tasks, RPA frees up recruiters to focus on more creative and strategic work. AI and predictive analysis then proactively strengthens HR processes, allowing the organisation to cultivate its talent and plan for its long-term manpower needs.